声明
TABLE OF CONTENTS
LIST OF TABLES AND FIGURES
ABSTRACT
摘要
Chapter 1：INTRODUCTION
1．1 Background
1．2 The significance of the Study
1．4 Literature review
1．5 Postharvest processes
1．6 Sorting and grading
1．7 Manual inspection
1．8 Machine vision application
1．8．1 Controlled machine vision system
1．8．2 Machine vision upcoming trends
1．9 Defect and calyx detection
Chapter 2：AN IMPLEMENTATION OF A LOW-COST TOMATO SORTER BY A MONOCHROMATIC CAMERA AND ARDUINO
2．1 Introduction
2．2 Materials and methods
2．2．1 Design of the automated tomato sorting system
2．2．2 Feature Extraction and sorting Algorithm
2．3 Results and discussion
2．3．1 Tomato size sorting test
2．3．2 Tomato eolour sorting test
2．4 Conclusions
Chapter 3：A COMPUTER VISION SYSTEM FOR DEFECT DISCRIMINATION AND GRADING IN TOMATOES USING IMAGE PROCESSING AND MACHINE LEARNING
3．2 Materials and methods
3．3 Experiment setup and data collection
3．4 Image processing and feature extraction algorithms
3．5 Image processing
3．5．1 Background removal
3．5．2 Calyx and stalk scar detection and segmentation
3．5．3 Defect detection
3．6 Feature extraction
3．6．1 Color features
3．6．2 Texture features
3．6．3 Shape features
3．7 Recognition models
3．8 RESULTS AND DISCUSSION
3．9 Calyx and stalk scar detection evaluation
3．10 Defect detection evaluation
3．11 Grading categories evaluation
3．11．1 Two grades category(cat 1)grading
3．11．2 Three grades category(cat 2) grading
3．11．3 Three grades category(cat 3)grading
3．11．4 Five grades category(cat 4)grading
3．12 Extracted features evaluation
Chapter 4：CONCLUSION AND RECOMMENDATIONS
REFERENCES
RESEARCH PAPERS PUBLICATIONS
ACKNOWLEDGEMENTS
APPENDIX
南京农业大学;
